True Experimental Nonexperimental True Experimental Design In true experimental design, one group gets the intervention or program and another group does not. Selection can play a part when participants themselves choose to enroll in a program self-selection , since those who decide to participate are probably already motivated to make changes. Given the range of community programs that exist, there are many possibilities here. In a retrospective design, the participant takes both a pretest and a posttest after the intervention is complete. In reality, an experiment is just trying something out to see how or why or whether it works. The design depends on what kinds of questions your evaluation is meant to answer. Retrospective Design in Practice A program coordinator wants to determine how participating in a one-day health clinic and prevention workshop for homeless youth intervention has impacted youth knowledge about specific health risks. Time-series designs look for changes over time to determine trends.
There are other reasons that participants might object to observation, or at least intense observation. A control group design is usually the most difficult to set up — you have to find appropriate groups, observe both on a regular basis, etc.
The W. Chapter 3 of the GAO Designing Evaluations handbook focuses on the process of selecting an evaluation design.
There are probably relatively few community programs where evaluation is this easy — you might, for instance, want to know which of your pollution-control activities is most effective — but if yours is one, a simple design may be all you need. Evaluators observe the intervention group multiple times before and after the intervention and analyze trends before and after.
You may be able to overcome these obstacles, or you may have to compromise — fewer or different kinds of observations, a less intrusive design — in order to be able to conduct the evaluation at all.
Evaluation designs public health
Posttest Only Design A posttest only design is simple, straightforward, and can be done with one group no comparison group or two groups with a comparison group of participants. They usually refer to procedures that have results that can be translated into numbers, and may take the form of community assessments, observations, surveys, interviews, or tests. If, for instance, the two groups come from the same pool of people with a particular health condition, and are chosen at random either to be treated in the conventional way or to try a new approach, it can be assumed that — since they were chosen at random from the same population — both groups will be subject, on average, to the same outside influences, and will have the same diversity of backgrounds. High rates of dropouts in the intervention or comparison groups can bias the results. Practical difficulties arise in randomly assigning subjects to the intervention and comparison groups, and it may be unethical to offer the intervention to one group but not to another group. Since a control group is more rigorously designed than a comparison group, participants likely receive none of an intervention and are matched on very specific qualities and characteristics. Pre- and post- single-group design The simplest design is also probably the least accurate and desirable: the pre before and post after measurement or observation. An instrument — a blood pressure cuff or a scale, for instance — can change over time, or different ones may not give the same results. Work Group for Community Health and Development. These individuals serve as their own controls—characteristics of an individual observed earlier can be controlled for when analyzing changes in the outcomes.
The longitudinal study is another type of time-series design. Research designs, in general, differ in one or both of two ways: the number and timing of the measurements they use; and whether they look at single or multiple groups.
The same is true for participants. This material is meant only to give you a sense of how to start thinking about the issue of design for an evaluation. The availability of professional evaluators.
Evaluation design ppt
While they contain too much material to summarize here, there are some basic designs that we can introduce. Participants may change behavior as a result of being observed, or may react to particular individuals in ways they would be unlikely to react to others. When randomization of subjects or groups is neither practical nor feasible, a quasi-experimental design can approximate the randomized experiment. Some of the most common: Program structure. From the Introduction to Program Evaluation for Public Health Programs, this resource from CDC on Focus the Evaluation Design offers suggestions for tailoring questions to evaluate the efficiency, cost-effectiveness, and attribution of a program. Retrospective Design in Practice A program coordinator wants to determine how participating in a one-day health clinic and prevention workshop for homeless youth intervention has impacted youth knowledge about specific health risks. A partnership with a nearby university could get you not only expertise, but perhaps needed equipment as well. There are probably relatively few community programs where evaluation is this easy — you might, for instance, want to know which of your pollution-control activities is most effective — but if yours is one, a simple design may be all you need. Randomized studies are often expensive to implement, which may limit the feasibility of this design for many health programs. Consider your evaluation questions What do you need to know? Organization s : Centers for Disease Control and Prevention Website Describes why evaluations are important, frameworks for program evaluation, and standards for developing a strong program evaluation. Just how precise you can be is at least partially controlled by the limits on your time placed by funding, program considerations, and other factors. The interference of multiple treatments or interventions. Understanding your program to this extent makes it easier to achieve and maintain success.
Instead, data are collected only after the program has ended among participants who had received the intervention and among non-participants, making for a weaker design. You may have to collect data to try and control for potential differences as part of your statistical analyses.
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